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Optimization & Theory

43,292 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

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52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Distribution Aware Metrics for Conditional Natural Language Generation COLING 2024 Distribution Learning via Neural Differential Equations: A Nonparametric Statistical Perspective JMLR 2024 Distribution Learning with Valid Outputs Beyond the Worst-Case NeurIPS 2024 DistrictNet: Decision-aware learning for geographical districting NeurIPS 2024 DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving OSDI 2024 DITTO: Diffusion Inference-Time T-Optimization for Music Generation ICML 2024 Divergent Token Metrics: Measuring degradation to prune away LLM components – and optimize quantization NAACL 2024 Diverse Projection Ensembles for Distributional Reinforcement Learning ICLR 2024 Diversify, Contextualize, and Adapt: Efficient Entropy Modeling for Neural Image Codec NeurIPS 2024 Diversity-Driven Synthesis: Enhancing Dataset Distillation through Directed Weight Adjustment NeurIPS 2024 Divide-and-Conquer Posterior Sampling for Denoising Diffusion priors NeurIPS 2024 Divide-Conquer-Reasoning for Consistency Evaluation and Automatic Improvement of Large Language Models EMNLP 2024 Divide-or-Conquer? Which Part Should You Distill Your LLM? EMNLP 2024 DL-QAT: Weight-Decomposed Low-Rank Quantization-Aware Training for Large Language Models EMNLP 2024 DN-4DGS: Denoised Deformable Network with Temporal-Spatial Aggregation for Dynamic Scene Rendering NeurIPS 2024 DNA-SE: Towards Deep Neural-Nets Assisted Semiparametric Estimation ICML 2024 DNGaussian: Optimizing Sparse-View 3D Gaussian Radiance Fields with Global-Local Depth Normalization CVPR 2024 DNNLasso: Scalable Graph Learning for Matrix-Variate Data AISTATS 2024 DNSMOS Pro: A Reduced-Size DNN for Probabilistic MOS of Speech Interspeech 2024 Do Androids Know They’re Only Dreaming of Electric Sheep? ACL 2024 DocMath-Eval: Evaluating Math Reasoning Capabilities of LLMs in Understanding Long and Specialized Documents ACL 2024 Does CLIP Bind Concepts? Probing Compositionality in Large Image Models EACL 2024 Does Pre-trained Language Model Actually Infer Unseen Links in Knowledge Graph Completion? NAACL 2024 Does Worst-Performing Agent Lead the Pack? Analyzing Agent Dynamics in Unified Distributed SGD NeurIPS 2024 DOGE: Domain Reweighting with Generalization Estimation ICML 2024